Abstract #0128

Improving K-T Auto-Calibrating Parallel Imaging for 3D Cardiac Cine MRI Using Prior-Reconstruction Static Tissue Estimation and Elimination

Peng Lai¹, Shreyas S. Vasanawala², Atsushi Nozaki³, Maggie Fung⁴, Anja C.S Brau⁵

¹MR Applications & Workflow , GE Healthcare, Menlo Park, CA, United States; ²Radiology, Stanford University, Stanford, CA, United States; ³MR Applications & Workflow, GE Healthcare, Asahigaoka, Hino, Japan; ⁴MR Applications & Workflow, GE Healthcare, Jersey City, NJ, United States; ⁵MR Applications & Workflow, GE Healthcare, Garching, Munchen, Germany

High acceleration needed for 3D cine MRI potentially results in residual artifacts. High density coils and k-t acceleration methods demand long reconstruction time. In this work, we developed a method that automatically estimates and eliminates static tissue signals from k-t accelerated 3D cine datasets. This method enables k-t reconstruction on dynamic tissue signals with reduced aliasing and furthermore enables selective reconstruction on locations and coil channels around the heart only. Based on our evaluations, the proposed method can improve 3D cardiac cine MRI in both image quality and computation efficiency.